As an expert in conversational AI safety and oversight, I closely track new systems like Claude 2 that promise to advance trust in the field. Naturally there is much interest among researchers on if and when advanced models like Claude will be fully transparent. This article analyzes that complex issue.
Claude 2: Constitutional AI for Helpful, Harmless, and Honest Assistants
I have had opportunity to work directly with Claude across multiple versions. A distinguishing capability is constitutional AI, instilling conversational safeguards directly into the models. For example, Claude refuses requests that may violate ethics or cause potential harms.
Anthropic has raised over $700M, enabling significant resourcing, with over 140 PhD researchers on staff drawn from top AI programs. They target a standard well beyond today‘s large language models in safety.
Powerful Generative AI Merits Responsible Openness Standards
As an open source advocate, I firmly believe that maximum transparency around any influential technology facilitates accountability and trust. Ethically, any system impacting millions should be subject to public inspection.
However, economically viable incentives still matter – years of effort deserve potential returns. And legally, IP rights establish exclusivity periods deemed reasonable for recovering investment.
So there are merits to arguments on all sides. With rapidly advancing AI, we need nuanced perspective on balancing openness and constraints.
Risks and Challenges Opening Generalized AI Too Early
We already see challenges governance scalable content moderation by Big Tech. Now we introduce exponentially more powerful generative AI. Before unleashing such computational creativity completely open, unconstrained, we should consider:
Potential for nefarious use
- Synthetic disinformation tailored to manipulate at scale
- Impersonation for scams and social engineering
- Generate harmful, abusive, dangerous content on demand
Accountability gaps
- Dissemination by anonymous foreign actors
- Auto-evolving offensive content via code modification
- Unclear liability with decentralized distribution
There are merits for responsible restraint until readiness. We still struggle governing social media platforms. Generalized AI poses much more acute challenges.
A Staged Roadmap Towards Transparency Is Needed
Rather than a false dichotomy of completely open versus permanantly closed, we need a staged roadmap:
Phase 1
- Documentation of intended use cases, risk assessments
- Release narrowed versions for non-sensitive domains
- Establish open version control and bug bounties
Phase 2
- Setup external oversight and audit board access
- Sunrise clauses enabling monitoring before full deployment
Phase 3
- Release moderated access for accredited parties
- Mandate liability constraints on downstream developers
This allows incremental opening based on evidence of societal readiness.
My Position: We Must Get This Right
In my direct experience, while the promise of trusted AI like Claude is exciting, unconstrained openness risks unintended consequences at the onset. Measured steps towards transparency, keeping pace with governance solutions, is vital for positive outcomes.
Advanced AI will keep advancing. The genie does not return to the bottle. Our choice is how to integrate responsibly. That requires insight and forethought by all of us in this field focused on the human impacts ahead.
